SOTAVerified

Dimensionality Reduction

Dimensionality reduction is the task of reducing the dimensionality of a dataset.

( Image credit: openTSNE )

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 2341–2350 of 3304 papers

TitleStatusHype
UNO-QA: An Unsupervised Anomaly-Aware Framework with Test-Time Clustering for OCTA Image Quality Assessment—0
Toward Unsupervised Test Scenario Extraction for Automated Driving Systems from Urban Naturalistic Road Traffic Data—0
Unsupervised Acoustic Scene Mapping Based on Acoustic Features and Dimensionality Reduction—0
Unsupervised Anomaly Segmentation using Image-Semantic Cycle Translation—0
Unsupervised Bump Hunting Using Principal Components—0
Unsupervised Construction of Knowledge Graphs From Text and Code—0
Unsupervised Data-Driven Nuclei Segmentation For Histology Images—0
Unsupervised Deep Haar Scattering on Graphs—0
Unsupervised Dimension Selection using a Blue Noise Spectrum—0
fMBN-E: Efficient Unsupervised Network Structure Ensemble and Selection for Clustering—0
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All datasetsMCAEMNIST

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1UDRNClassification Accuracy90.9—Unverified
2tSNEClassification Accuracy51.5—Unverified
3IVISClassification Accuracy46.6—Unverified
4UMAPClassification Accuracy41.3—Unverified
#ModelMetricClaimedVerifiedStatus
1UDRNClassification Accuracy71.1—Unverified
2QSClassification Accuracy68—Unverified